---
type: entity
entity_type: research_program
name: SPAR Automating Circuit Interpretability with Agents
status: active
founded: 2025
parent_org: SPAR (Scalable Alignment Research)
domain: ai-alignment
supports:
- Circuit tracing requires hours of human effort per prompt which creates a fundamental bottleneck preventing interpretability from scaling to production safety applications
reweave_edges:
- Circuit tracing requires hours of human effort per prompt which creates a fundamental bottleneck preventing interpretability from scaling to production safety applications|supports|2026-04-08
---

# SPAR Automating Circuit Interpretability with Agents

Research program targeting the human analysis bottleneck in mechanistic interpretability by using AI agents to automate circuit interpretation work.

## Overview

SPAR's project directly addresses the documented bottleneck that 'it currently takes a few hours of human effort to understand the circuits even on prompts with only tens of words.' The program attempts to use AI agents to automate the human-intensive analysis work required to interpret traced circuits, potentially enabling interpretability to scale to production safety applications.

## Approach

Applies the role specialization pattern from human-AI mathematical collaboration to interpretability work, where AI agents handle the exploration and analysis while humans provide strategic direction and verification.

## Timeline

- **2025** — Program initiated to address circuit tracing scalability bottleneck
- **2026-01** — Identified by Mitra as the most direct attempted solution to the hours-per-prompt constraint